The statements in the background of the invention are provided to assist with understanding the invention and its applications and uses, and may not constitute prior art.
There are many applications where measuring the height of an object, such as a human being, using just a camera device on a mobile computing device would be highly desirable. For example, one illustrative application includes accurately tracking a child's growth, using just photographs taken of the child taken with an ordinary smartphone. Another illustrative application includes measuring the height of a piece of furniture, such as a table, using just a photograph taken of the table with a mobile device while shopping.
Another application is in the field of e-commerce for online retailers desiring accurate body measurements, including the height of the shopper. One instance where 3D measurements from images are vital includes identifying clothing sizes for shoppers. There have been several approaches that have been tried to extract 3D measurements from images of 3D objects, including utilizing specialized 3D cameras as well as utilizing 2D videos or 2D photos, followed by 2D-to-3D reconstruction techniques to estimate 3D measurements.
One new technique for 3D measurements, described in U.S. Pat. No. 10,321,728 referenced above, is to utilize deep learning networks to extract measurements from 2D photos taken using a single mobile device camera. This technique minimizes user frictions while promising to deliver highly accurate measurements. 2D photos can be very useful in situations where the 3D object is not physically present to provide measurements. However, in order to obtain accurate measurements, some size reference is needed. For example, in the case of body measurements, the user is required to provide their own height in order to normalize the rest of the body measurements from pixel dimensions to real-world dimensions. However, many users don't have an accurate knowledge of their own height. Similarly, when obtaining measurements of other objects, physical scale guides or reference objects with standardized sizes, such as credit cards or A4 pieces of paper, need to be used in order to obtain accurate measurements. However, using physical scale guides or reference objects for obtaining measurements of 3D objects introduces unnecessary user frictions into the measurement process since a reference object with a known size has to be readily available.
Therefore, it would be an advancement in the state of the art to provide a method by which the height of an object, such as a user, may be accurately measured in real-world coordinates from just a single photograph taken of the object using an ordinary mobile device camera.
It is against this background that the present invention was developed.